
Data Complexity and the Value of Surprisal
Description
Data Complexity and the Value of Surprisal
The complexity of data is an important concept to understand, as it points to a source of value in data and helps explain why organizations are structured the way they are in order to extract this value from increasingly complex data. Bearing this in mind, while it is easier to target technology investments toward low-complexity procedural-type data processes, organizations that focus on managing more complex data containing increasing levels of surprisal, with technologies like AI, machine learning, digital twinning, and so forth, can see economic gains, said Thomas Jackson, research director of IDC's Data Valuation: Industry Perspectives Market Research and Advisory Service.
Please Note: Extended description available upon request.
The complexity of data is an important concept to understand, as it points to a source of value in data and helps explain why organizations are structured the way they are in order to extract this value from increasingly complex data. Bearing this in mind, while it is easier to target technology investments toward low-complexity procedural-type data processes, organizations that focus on managing more complex data containing increasing levels of surprisal, with technologies like AI, machine learning, digital twinning, and so forth, can see economic gains, said Thomas Jackson, research director of IDC's Data Valuation: Industry Perspectives Market Research and Advisory Service.
Please Note: Extended description available upon request.
Table of Contents
5 Pages
- Executive Snapshot
- Situation Overview
- Data Complexity
- Data Surprisal = Value
- Decision Making in Complex Data Environments
- Advice for the Technology Buyer
- Learn More
- Related Research
- Synopsis
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